Identifying cancer drivers is a crucial challenge to explain the underlying mechanisms of cancer development. There are many methods to identify cancer drivers based on the single mutation site or the entire gene. But they ignore a large number of functional elements with medium in size. It is hypothesized that mutations occurring in different regions of the protein sequence have different effects on the progression of cancer. Here, we develop a novel functional region driver(frDriver) identification method based on Bayesian probability and multiple linear regression models to identify protein regions that can regulate gene expression levels and have high functional impact potential. Combining gene expression data and somatic mutation data, with functional impact scores(SIFT, PROVEAN) as a priori knowledge, we identified cancer driver regions that are most accurate in predicting gene expression levels. We evaluated the performance of frDriver on the BRCA and GBM datasets from TCGA. The results showed that frDriver identified known cancer drivers and outperformed the other three state-of-the-art methods(eDriver, ActiveDriver and OncodriveCLUST). In addition, we performed KEGG pathway and GO term enrichment analysis, and the results indicated that the cancer drivers predicted by frDriver were related to processes such as cancer formation and gene regulation.

中文翻译：

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frDriver：蛋白质序列的功能区域驱动识别

识别癌症驱动因素是解释癌症发展潜在机制的关键挑战。有许多方法可以根据单个突变位点或整个基因来识别癌症驱动因素。但他们忽略了大量中等大小的功能元素。据推测，发生在蛋白质序列不同区域的突变对癌症的进展有不同的影响。在这里，我们开发了一种基于贝叶斯概率和多元线性回归模型的新型功能区域驱动程序（frDriver）识别方法，以识别可以调节基因表达水平并具有高功能影响潜力的蛋白质区域。结合基因表达数据和体细胞突变数据，以功能影响评分（SIFT，PROVEAN）作为先验知识，我们确定了在预测基因表达水平方面最准确的癌症驱动区域。我们评估了 frDriver 在 TCGA 的 BRCA 和 GBM 数据集上的性能。结果表明，frDriver 识别出已知的癌症驱动因素，并且优于其他三种最先进的方法（eDriver、ActiveDriver 和 OncodriveCLUST）。此外，我们进行了KEGG通路和GO term富集分析，结果表明frDriver预测的癌症驱动因素与癌症形成和基因调控等过程有关。ActiveDriver 和 OncodriveCLUST）。此外，我们进行了KEGG通路和GO term富集分析，结果表明frDriver预测的癌症驱动因素与癌症形成和基因调控等过程有关。ActiveDriver 和 OncodriveCLUST）。此外，我们进行了KEGG通路和GO term富集分析，结果表明frDriver预测的癌症驱动因素与癌症形成和基因调控等过程有关。